scholarly journals Kinetic modeling predicts a role for ribosome collisions at elongation stall sites in bacteria

2016 ◽  
Author(s):  
Michael Ferrin ◽  
Arvind R. Subramaniam
Keyword(s):  
Translation Initiation ◽  
Amino Acid Starvation ◽  
Fine Tuning ◽  
Initiation Rate ◽  
Translation Elongation ◽  
Kinetic Rate ◽  
Inverse Approach ◽  
Ribosome Stalling ◽  
Traffic Jams ◽  
Reporter Mrna

AbstractRibosomes can stall during translation elongation in bacteria and eukaryotes. To identify mechanisms by which ribosome stalling affects expression of the encoded protein, we develop an inverse approach that combines computational modeling with systematic perturbations of translation initiation rate, the number of stall sites, and the distance between stall sites on a reporter mRNA. By applying this approach to ribosome stalls caused by amino acid starvation in the bacteriumEscherichia coli, we find that our measurements are quantitatively inconsistent with two widely used kinetic models for stalled ribosomes: ribosome traffic jams that block initiation, and abortive (premature) termination of stalled ribosomes. To account for this discrepancy, we consider a model in which collision from a trailing ribosome causes abortive termination of the stalled ribosome. This collision-stimulated abortive termination model provides a better fit to measured protein synthesis rates from our reporter library, and is consistent with observed ribosome densities near stall sites. Analysis of this model further predicts that ribosome collisions can selectively stimulate abortive termination of stalled ribosomes without fine-tuning of kinetic rate parameters. Thus ribosome collisions may serve as a robust timer for translational quality control pathways to recognize stalled ribosomes.

scholarly journals Kinetic modeling predicts a stimulatory role for ribosome collisions at elongation stall sites in bacteria

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Michael A Ferrin ◽  
Arvind R Subramaniam
Keyword(s):  
Escherichia Coli ◽  
Quality Control ◽  
Protein Synthesis ◽  
Translation Initiation ◽  
Computational Analysis ◽  
Fine Tuning ◽  
Initiation Rate ◽  
Kinetic Rate ◽  
Ribosome Stalling ◽  
Traffic Jams

Ribosome stalling on mRNAs can decrease protein expression. To decipher ribosome kinetics at stall sites, we induced ribosome stalling at specific codons by starving the bacterium Escherichia coli for the cognate amino acid. We measured protein synthesis rates from a reporter library of over 100 variants that encoded systematic perturbations of translation initiation rate, the number of stall sites, and the distance between stall sites. Our measurements are quantitatively inconsistent with two widely-used kinetic models for stalled ribosomes: ribosome traffic jams that block initiation, and abortive (premature) termination of stalled ribosomes. Rather, our measurements support a model in which collision with a trailing ribosome causes abortive termination of the stalled ribosome. In our computational analysis, ribosome collisions selectively stimulate abortive termination without fine-tuning of kinetic rate parameters at ribosome stall sites. We propose that ribosome collisions serve as a robust timer for translational quality control pathways to recognize stalled ribosomes.

scholarly journals Translation Initiation Rate Determines the Impact of Ribosome Stalling on Bacterial Protein Synthesis

2014 ◽  
Vol 289 (41) ◽  
pp. 28160-28171 ◽  
Author(s):  
Steven J. Hersch ◽  
Sara Elgamal ◽  
Assaf Katz ◽  
Michael Ibba ◽  
William Wiley Navarre
Keyword(s):  
Protein Synthesis ◽  
Translation Initiation ◽  
Bacterial Protein ◽  
Initiation Rate ◽  
Ribosome Stalling ◽  
Bacterial Protein Synthesis ◽  
The Impact

scholarly journals Activation of GCN2 kinase by ribosome stalling links translation elongation with translation initiation

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Ryuta Ishimura ◽  
Gabor Nagy ◽  
Ivan Dotu ◽  
Jeffrey H Chuang ◽  
Susan L Ackerman
Keyword(s):  
Transcription Factor ◽  
Stress Response ◽  
Signaling Pathways ◽  
Translation Initiation ◽  
Transcriptome Analysis ◽  
Cellular Stress ◽  
Translation Elongation ◽  
Ribosome Stalling ◽  
Eif2α Kinase ◽  
The Brain

Ribosome stalling during translation has recently been shown to cause neurodegeneration, yet the signaling pathways triggered by stalled elongation complexes are unknown. To investigate these pathways we analyzed the brain of C57BL/6J-Gtpbp2nmf205-/- mice in which neuronal elongation complexes are stalled at AGA codons due to deficiencies in a tRNAArgUCU tRNA and GTPBP2, a mammalian ribosome rescue factor. Increased levels of phosphorylation of eIF2α (Ser51) were detected prior to neurodegeneration in these mice and transcriptome analysis demonstrated activation of ATF4, a key transcription factor in the integrated stress response (ISR) pathway. Genetic experiments showed that this pathway was activated by the eIF2α kinase, GCN2, in an apparent deacylated tRNA-independent fashion. Further we found that the ISR attenuates neurodegeneration in C57BL/6J-Gtpbp2nmf205-/- mice, underscoring the importance of cellular and stress context on the outcome of activation of this pathway. These results demonstrate the critical interplay between translation elongation and initiation in regulating neuron survival during cellular stress.

scholarly journals Fine-tuning biosensor dynamic range based on rational design of cross-ribosome-binding sites in bacteria

2020 ◽  
Author(s):  
Nana Ding ◽  
Shenghu Zhou ◽  
Zhenqi Yuan ◽  
Xiaojuan Zhang ◽  
Jing Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Deep Learning ◽  
Translation Initiation ◽  
Rational Design ◽  
Dynamic Range ◽  
Regulatory Elements ◽  
Fine Tuning ◽  
Initiation Rate ◽  
Ribosome Binding

ABSTRACTCurrently, predictive translation tuning of regulatory elements to the desired output of transcription factor based biosensors remains a challenge. The gene expression of a biosensor system must exhibit appropriate translation intensity, which is controlled by the ribosome-binding site (RBS), to achieve fine-tuning of its dynamic range (i.e., fold change in gene expression between the presence and absence of inducer) by adjusting the translation initiation rate of the transcription factor and reporter. However, existing genetically encoded biosensors generally suffer from unpredictable translation tuning of regulatory elements to dynamic range. Here, we elucidated the connections and partial mechanisms between RBS, translation initiation rate, protein folding and dynamic range, and presented a rational design platform that predictably tuned the dynamic range of biosensors based on deep learning of large datasets cross-RBSs (cRBSs). A library containing 24,000 semi-rationally designed cRBSs was constructed using DNA microarray, and was divided into five sub-libraries through fluorescence-activated cell sorting. To explore the relationship between cRBSs and dynamic range, we established a classification model with the cRBSs and average dynamic range of five sub-libraries to accurately predict the dynamic range of biosensors based on convolutional neural network in deep learning. Thus, this work provides a powerful platform to enable predictable translation tuning of RBS to the dynamic range of biosensors.

scholarly journals Detailed Dissection and Critical Evaluation of the Pfizer/BioNTech and Moderna mRNA Vaccines

Vaccines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 734
Author(s):  
Xuhua Xia
Keyword(s):  
Codon Usage ◽  
Translation Initiation ◽  
Mrna Stability ◽  
Stop Codon ◽  
Translation Termination ◽  
Critical Evaluation ◽  
Immunization Programs ◽  
Translation Elongation ◽  
Different Types ◽  
Similarities And Differences

The design of Pfizer/BioNTech and Moderna mRNA vaccines involves many different types of optimizations. Proper optimization of vaccine mRNA can reduce dosage required for each injection leading to more efficient immunization programs. The mRNA components of the vaccine need to have a 5’-UTR to load ribosomes efficiently onto the mRNA for translation initiation, optimized codon usage for efficient translation elongation, and optimal stop codon for efficient translation termination. Both 5’-UTR and the downstream 3’-UTR should be optimized for mRNA stability. The replacement of uridine by N1-methylpseudourinine () complicates some of these optimization processes because is more versatile in wobbling than U. Different optimizations can conflict with each other, and compromises would need to be made. I highlight the similarities and differences between Pfizer/BioNTech and Moderna mRNA vaccines and discuss the advantage and disadvantage of each to facilitate future vaccine improvement. In particular, I point out a few optimizations in the design of the two mRNA vaccines that have not been performed properly.

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